System and methods for improved diabetes data management and use employing wireless connectivity between patients and healthcare providers and repository of diabetes management information

ABSTRACT

Methods, devices and a system for disease management are provided that employ diagnostic testing devices (e.g., blood glucose meters) and medication delivery devices (e.g., insulin delivery devices) for providing data to a repository in real-time and automatically. Repository data can be analyzed to determine such information as actual test strip use, patient health parameters to outside prescribed ranges, testing and medication delivery compliance, patient profiles or stakeholders to receive promotional items or incentives, and so on. Connected meters and medication delivery devices and repository data analysis are also employed to associate a diagnostic test to a mealtime based on timing of a therapeutic intervention performed by an individual.

This application claims the benefit under 35 U.S.C. §119(e) of U.S.provisional patent application Ser. No. 60/784,760, filed Mar. 23, 2006.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention generally relates to improved methods, devices andsystem for disease management. More particularly, the present inventionrelates to real-time communication of data between devices (e.g., bloodglucose meters, insulin delivery devices) and a repository and analysisof repository data to obtain information to improve disease managementand provide cost savings to disease management stakeholders.

2. Description of the Related Art

FIG. 1 illustrates an existing system 10 for diabetes management. Forconvenience, the following abbreviations shall be used herein:

BGM blood glucose meter

DM diabetes management

DMC disease management companies

DMD diabetes management data

WM wireless BGM

As shown in FIG. 1, a patient 12 performs blood glucose monitoring(e.g., using lancets and a BGM 18 with test strips, or a continuousmeter) and administers insulin injections (e.g., via a syringe, pen orpump 20) as needed. The BGM and the insulin injections are typicallyrecorded manually in a notebook 22 by the patient or his or hercaregiver to share with a healthcare provider such as a doctor 14 or adisease management company 16. This information is typically shared viatelephone (e.g., telephone 26, 28 and 32), computer (e.g., computers 24and 30), or in person during office visits. This information can alsoinclude information relating to diet, exercise and other factors thatinfluence diabetes management outcomes. Unfortunately, this informationis not verified and often not recorded, collected or managed in areliable and cohesive manner to be useful to the patient's healthcareteam in facilitating optimal diabetes management.

With continued reference to FIG. 1, diabetes management data such asblood glucose tests and insulin intake can be recorded using a personalcomputer (PC) 24, as opposed to handwritten record keeping 22, oruploaded to a patient's PC 24 from a device (e.g., a blood glucose meter18 or insulin delivery pen 20) using a software interface. Conventionalcommunications interfaces, however, are inconvenient because a patient12 must acquire a communication interface such as a specialized modemand/or install software on a PC 24 to upload data from a BGM 18.Further, such PC interfaces for diabetes data management do notnecessarily allow the entered data to be shared with other stakeholdersin diabetes management and care, that is, physicians and otherhealthcare providers 14, insurers, or disease management companies(DMCs) 16 that are typically hired by employers or insurance companies,as indicated by the optional lines shown in phantom in FIG. 1. Ifdiabetes management data from a patient 14 can be provided to ahealthcare team member's PC 30, that information is generally notrecorded in a comprehensive manner that assures completeness, accuracyand timeliness of the data. For example, quite often patients 14 fail totest, or to write down, enter or upload a blood glucose test result orinsulin injection, leaving healthcare team members 30 and 16 withincomplete information and not allowing them to identify teachablemoments or events in diabetes management or respond in real-time.

Similarly, special cradles such as GlucoMON by Diabetech in Dallas,Tex., are currently available to get data from a patient 14 securely toother people. Diabetech makes the device and manages the service totransmit blood glucose test results to selected people, typically viacell phone, pager, or e-mail, according to the instructions of thepatient 14 or their legal guardian. This data, however, is merelyreported to selected persons and not collected and managed in acomprehensive manner. Additionally, this system requires that the user14 acquire and connect a secondary device to their BGM 18. Thus, a needexists for an integrated device for monitoring glucose levels andreporting same to other stakeholders in diabetes management and care.

Cell phones combined with diabetes data management functions have beenproposed, not surprisingly in an era of increasingly indispensablepersonal electronic devices. For those with chronic conditions such asdiabetes, technical convergence of healthcare and personal electronictechnology makes even more sense to facilitate use of medications,meters, pumps, injections, and the need to carefully track and documentimportant health data, particularly for those with chronic conditionsthat require significant self-management.

Several medical companies are developing smarter, more convenientmonitoring equipment and are using telecommunications technology tocreate multipurpose, portable devices for patient use. One of thesecompanies is HealthPia America, a Newark, N.J.-based telemedicineventure that has developed a cell phone that also serves as a bloodglucose monitor and features a pedometer. An embedded electronicbiosensor in the battery pack enables the cell phone to have a glucosemeter function. The sensor reads blood glucose levels from a strip. Thedata is then uploaded to the cell phone's display. The phone can beprogrammed to send the information instantly to a health care provider14, parent, or guardian. Movement and exercise also can be monitoredwith the built-in pedometer. The phone can be programmed to send analert to the caregiver or clinician via short-message service if thereis no pedometer reading for a pre-programmed length of time. The caremanager can call back to check if the patient 12 is okay, and if thereis no response, prearranged emergency procedures can be initiated. Thisfeature could be especially useful for detecting insulin reactions orsevere hypoglycemia in diabetes patients 12. The biggest advantage ofthe Diabetes Phone is its alarm features, which allow a physician to setspecific parameters. If the phone reports continuously high bloodglucose, for example, a doctor can react in real-time.

Other diabetes cell-phone projects include research at Oxford Universityin the U.K. to test a system similar to that of HealthPia America. Inanother venture, British patients 12 with diabetes have been able toregister since 2002 with Sweet Talk, a message service that reminds themvia cell phone to take their insulin and offers general education aboutliving with diabetes. Further, in 2003, IBM announced that its“Bluetooth” short-range wireless technology could be used to intercept aperson's 12 heart rate and send it to a cell phone.

At the ITU Telecom Asia 2004 show in Korea, LG Electronics showed anovel handset, the KP8400. The KP8400 is designed for diabetics and iscapable of doing blood sugar level tests just as would a dedicateddevice. Users 12 place a strip of testing paper into the sensor locatedin the phone's battery pack, place a drop of blood on the end of thestrip, and then get a reading from the phone. The reading can then beuploaded to an online database for later retrieval. LG Electronics has astrategic alliance with Healthpia Co., Ltd. to implement the KP8400.

Whether these new and proposed electronic devices for diabetesmanagement will result in their widespread adoption and better self-carefor patients 12, or simply more work for clinicians 14 as they strive tomanage a new stream of information, is the central question as this newfrontier of electronic medicine is explored. For example, the datareported by one of these emerging cell phone technologies does notappear to be managed in a cohesive manner such that the real-time testresults can be associated with other information such as test trip lotnumber and use verification, or mealtime events and therapy intervention(e.g., insulin injection), and the like.

Further, what is largely overlooked is the value to less traditionalstakeholders in the business of DM. A need therefore exists for businessmodels, methods and apparatuses that maximize the value of collected DMDfor various stakeholders such as disease management companies 16,insurers and healthcare networks.

As stated above, disease management companies 16 are typically hired bya patient's insurer or employer to provide the patient 12 witheducational support for their disease. DMCs obtain claims data such asprescriptions and visits to healthcare providers 14, as well as otherdata such as BG measurements, insulin dosages, diet and exercise. Muchof this information is collected from the patient 12 via telephone(e.g., telephones 26, 28 and 32) which is problematic for a number ofreasons. For whatever reasons, patients are often not completelytruthful with their healthcare providers 14 and DMC 16 representativeabout their DM lifestyle choices (e.g., diet, exercise, BG testing andmedicating with insulin). Some of the reasons are inadequate educationabout diabetes self-management, apathy, embarrassment, economicbarriers, lack of proficiency in testing and use of data interfaceequipment, or faulty equipment or testing technique (e.g., poor timingwith respect to meal times).

A need therefore exists for a diabetes data management system thatallows DMCs 16 and other third parties (e.g., insurance companies,Medicare, Medicaid, HMOs, etc.) to provide patients 12 with incentivesto take better care of themselves and manage their diabetes andotherwise improve their outcomes. For example, a need exists for asystem that can monitor and have verification of a patient's actualblood glucose monitoring practices. A DMC 16 can then, for example,remove economic barriers by giving patients, who have shown progress inmanaging their diabetes, test strips and/or a blood glucose monitor atnominal cost or no charge or by waiving their co-pays.

Currently, reimbursement for diabetes testing supplies by third parties(e.g., insurance companies, Medicare, Medicaid, HMOs, etc.) is based ona model where a specific number of BGM test strips are covered dependingon the patient's condition (e.g., a person 12 with diabetes who requiresinsulin injections to help manage their diabetes may have coverage for60 BGM test strips per month (2 per day); or a person 12 with diabeteswho uses an oral medication to help manage their diabetes may havecoverage for 30 BGM test strips per month (1 per day).) In this model,the refill of a BGM test strip prescription is the only indication ofuse of the BGM test strips. However, this does not provide any objectiveevidence: a) that the patient 12 actually tested their blood glucoseusing the BGM test strips; b) that the tests were done at appropriatetimes; c) of the results of any tests that were done. In somesituations, patients 12 may “stockpile” their test strips or providethem to other family members or friends who do not have equivalentinsurance coverage for their needs. In these cases, the third partypayor is making payments for testing supplies that are not being used ornot being used appropriately. In this model, for example, the mail ordersupplies company and, ultimately, the BGM test strip manufacturerbenefit because they are paid by the third parties for all test stripsthat are delivered to the patient regardless of the patient's actualuse. A need therefore exists for a “pay for results” model wherein apayor pays for only those strips that are actually used.

SUMMARY OF THE INVENTION

Aspects of the exemplary embodiments of the present invention address atleast the above problems and/or disadvantages and provide at least theadvantages described herein.

For example, an exemplary embodiment of a DM system is provided thatsimplifies patient involvement with DMD reporting by automating sharingof collected data among other stakeholders. Preferably, there is nopatient involvement in the automated data movement (e.g., not even theneed to press a “Send” button to upload BG measurement data to astakeholder, or the more user-intensive option of connecting their BGMdevice to a computer or other communications device).

An exemplary embodiment of a DM is provided that improves patientcompliance for record-keeping and sharing information with healthcareproviders. For example, data collected accurately reflects status ofpatient and obviates failure to test for or reporting of events ofinterest to stakeholders, use of bad test strips, etc.

Exemplary embodiments of DM system business models are provided thatemphasize payors' use of data and not only patients' use of data, andemphasizes the value of the DMD versus the devices used to collect thedata.

Real-time reporting of event data relative to a stakeholder is providedin accordance with exemplary embodiments of the present invention. Atransaction is tailored to use (e.g., 100% real-time upload but lessthan real-time for retrieval and access, depending on which stakeholderis involved).

Exemplary embodiments of BGM devices are simplified to be displaydevices and whose analytical capabilities for generating averages andtrend data are moved to a repository level. The devices therefore becomeless complex, which provides a number of benefits (e.g., reduceddevelopment time and therefore time to market; and reduced complexityand thereby reduced potential for safety hazards). Simplified BGMdevices also increases useable life of the device because software“upgrades” are performed at the repository level, and not at the devicelevel. These simplified devices do not have to be replaced as often dueto upgrades because device firmware upgrades can be performedwirelessly. For example, instead of upgrading a memory module, thedevice can be provided with FLASH memory to receive upgrades from arepository over a communication network.

The exemplary embodiments of the present invention replace the currentstate of reimbursement for test supplies model with a “pay-for-result”model of doing business and realizes many advantages.

The exemplary embodiments of the present invention provide severalbusiness models, methods and apparatuses for maximizing the value ofcollected DMD for various stakeholders such as disease managementcompanies, insurers and healthcare networks.

In accordance with an exemplary embodiment of the present invention, aninsulin delivery system is provided comprising: an insulin deliverydevice comprising at least one of a syringe, a microneedle, a pump andan insulin pen configured to deliver insulin, an RFID tag connected tothe insulin delivery device for transmitting an insulin delivery deviceidentification number corresponding to the insulin delivery device andfor storing insulin delivery device data comprising insulin-typedelivered via the insulin delivery device, and a blood glucose metercomprising an RFID reader for activating the RFID tag to collect atleast the insulin delivery device data, and a wireless communicationcircuit configured for wireless communication with a repository fortransmitting data relating to insulin delivered by the insulin deliverydevice to the repository automatically and substantially in real-timewithout user involvement.

In accordance with another exemplary embodiment of the presentinvention, a method of monitoring test strip usage comprises: storingtesting data for patients in a repository, the testing data comprisingfor respective patients at least one of the number of recommended testsper day and the number of test strips allotted to the patient via one ofa supplier and an insurer, automatically transmitting test results froma blood glucose meter to the repository without user involvement, thetest results comprising measured glucose level, and comparing thetesting data and the test results stored in the repository for at leasta selected one of the patients to determine at least one of the numberof test strips actually used by the patient and the number of allottedtest strips that are unused within a selected time period.

In accordance with an exemplary embodiment of the present invention, amethod of using diagnostic data comprises: receiving therapy data andcorresponding time stamps for when different therapy events wereadministered to a patient, receiving diagnostic test data andcorresponding time stamps for when diagnostic tests were administered tothe patient, receiving parameters comprising respective time stamps forat least two of when the patient eats meals, sleeps and night-time testsare administered to the patient, and analyzing the therapy data timestamps, the diagnostic test data time stamps and the respective timestamps for at least two of when the patient eats meals, sleeps andnight-time tests are administered to the patient to associate a therapyevent with a test administered to a patient and at least one of ameal-time, bedtime, and night-time test. Alternatively, the method cancomprise receiving a parameter corresponding to a typical number ofmeals eaten per day, and then analyzing the therapy data time stamps,the diagnostic test data time stamps and the number of meals eaten perday to determine how the therapy data time stamps and the diagnostictest data time stamps cluster relative to the number of meals eaten perday for segmenting a day into mealtimes and categorizing the therapydata time stamps with respect to mealtimes.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and other objects, features, and advantages of certainexemplary embodiments of the present invention will be more apparentfrom the following detailed description, taken in conjunction with theaccompanying drawings in which:

FIG. 1 shows current flow of data and information between patients andtheir disease management devices and stakeholders;

FIG. 2 shows stakeholders in disease management and the typical flow ofinformation;

FIG. 3 shows wireless connectivity and RF communication pathway optionsto improve flow of data and information between patients and theirdisease management devices and stakeholders and a repository inaccordance with an exemplary embodiment of the present invention;

FIG. 4 is a block diagram of a repository in accordance with anexemplary embodiment of the present invention;

FIGS. 5A and 5B are perspective views of a wireless meter constructed inaccordance with an exemplary embodiment of the present invention;

FIG. 6 is a block diagram of a wireless meter constructed in accordancewith an exemplary embodiment of the present invention;

FIG. 7 is a block diagram of a wireless meter employing wireless USBconnectivity in accordance with an exemplary embodiment of the presentinvention;

FIG. 8 is a block diagram of a wireless meter employing WiFi or WiMaxconnectivity in accordance with an exemplary embodiment of the presentinvention;

FIG. 9 is a block diagram of a wireless meter employing Bluetooth orZigBee connectivity in accordance with an exemplary embodiment of thepresent invention;

FIGS. 10A and 10 are block diagrams of a wireless meter employing abuilt-in or cell modem attachment for connectivity in accordance with anexemplary embodiment of the present invention;

FIGS. 11A, 11B and 11C are, respectively, a perspective view, a top viewand a side view of a base station and meter in accordance with anexemplary embodiment of the present invention;

FIGS. 11D, 11E and 11F are respective views of a base station and meter,that is, a meter-only perspective view, and meter side view showing aport to connect with base station, and block diagram of docking stationcomponents and meter components with corresponding interfaces forconnection to each other, in accordance with an exemplary embodiment ofthe present invention;

FIGS. 12A and 12B are block diagrams of a base or docking station and ameter having connectivity to a repository directly or via a device inaccordance with an exemplary embodiment of the present invention;

FIGS. 13A, 13B and 13C are perspective side and back views of a BGM in acell phone in accordance with an exemplary embodiment of the presentinvention;

FIG. 14 is a block diagram showing connectivity of a BGM in a cell phonein accordance with an exemplary embodiment of the present invention;

FIGS. 15A, 15B, 15C and 15D illustrate a connected syringe in accordancewith an exemplary embodiment of the present invention;

FIGS. 16A, 16B, 16C, 16D and 16E illustrate a connected pen inaccordance with an exemplary embodiment of the present invention;

FIG. 17 is a block diagram showing connectivity of a pen or syringe inaccordance with an exemplary embodiment of the present invention;

FIGS. 18A and 18B illustrate a flow chart for use of test data by a DMCin accordance with an exemplary embodiment of the present invention;

FIG. 19 is a flow chart illustrating use of test data to control teststrip refills, promotional items and the like in accordance with anexemplary embodiment of the present invention;

FIG. 20 is a flow chart illustrating use of test data to enroll patientsin monthly service connectivity contract and manage incentivesdisbursements and the like in accordance with an exemplary embodiment ofthe present invention;

FIGS. 21A and B show, respectively, the front and back views of a bloodglucose monitor containing a radio frequency identification transponderin accordance with an exemplary embodiment of the present invention;

FIG. 22 shows a blood glucose test strip container with a radiofrequency identification transponder integrated into the outside labelin accordance with an exemplary embodiment of the present invention;

FIG. 23 shows a blood glucose test strip container with a radiofrequency identification transponder integrated into the cap inaccordance with an exemplary embodiment of the present invention;

FIG. 24 shows a blood glucose test strip with a radio frequencyidentification transponder as part of the test strip in accordance withan exemplary embodiment of the present invention;

FIG. 25 shows a system where the blood glucose monitor receives datafrom the test strip container and the test strip in accordance with anexemplary embodiment of the present invention;

FIG. 26 is a process flow chart for a parameter-based approach for usingtherapy times to classify diagnostic test data in accordance with anexemplary embodiment of the present invention;

FIG. 27 is a process flow chart for an analysis-based approach for usingtherapy times to classify diagnostic test data in accordance with anexemplary embodiment of the present invention;

FIG. 28 is a process flow chart for an analysis-based approach withfeedback loop for using therapy times to classify diagnostic test datain accordance with an exemplary embodiment of the present invention;

FIGS. 29, 30 and 31 illustrate the benefits of the connectivity andvalue added information provided by exemplary embodiments of the presentinvention in the context of overall patient and disease management;

FIGS. 32 through 37 illustrate current cash flows between DMstakeholders that can be improved by exemplary embodiments of thepresent invention in the context of overall patient and diseasemanagement;

FIGS. 38, 39 and 40 illustrate improvement over current cash flowsbetween DM stakeholders afforded by a pay-for-results model implementedin accordance with an exemplary embodiment of the present invention;

FIGS. 41A, 41B, 41C and 41D each illustrate a blood glucose monitor witha display message in accordance with an exemplary embodiment of thepresent invention; and

FIGS. 42 and 43 illustrate display screens generated for viewing via adisease management stakeholder computing device in accordance with anexemplary embodiments of the present invention.

Throughout the drawings, the same drawing reference numerals will beunderstood to refer to the same elements, features, and structures.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

The matters defined in the description such as a detailed constructionand elements are provided to assist in a comprehensive understanding ofthe embodiments of the invention. Accordingly, those of ordinary skillin the art will recognize that various changes and modifications of theembodiments described herein can be made without departing from thescope and spirit of the invention. Also, descriptions of well-knownfunctions and constructions are omitted for clarity and conciseness.

With regard to the present invention, the term “data” generally refersto numerical values such as blood glucose levels, times of day, dosageamounts, and so on. The term “information” generally refers toeducational information, feedback, qualitative status of patient,analysis of data, and so on. DMCs generally have proprietary algorithmsfor synthesizing information and data received from patients; however,this information and data is often faulty due to inadvertent orintentional misinformation from the patient, poor record keeping,failure to contact patient, and so on.

The present invention provides an improved DM system whereby sharing ofpatient DM-related data with other stakeholders is fully automated andreal-time. Further, improved access to more reliable patient DM data bythe other stakeholders allows for improved use of the information tofacilitate better management of the disease.

FIG. 2 illustrates the stakeholders in diabetes management. Thestakeholders are the patients and optionally their caregivers, theirhealthcare team members (e.g., physician), their insurers, theiremployers. As described above, a DMC 16 can be hired by a patient'sinsurer or employer to provide the patient 12 with educational supportfor his or her disease. DMCs 16 obtain medical claims data such asprescriptions and visits to healthcare providers, pharmacy data andlaboratory data, and then other data such as BG measurements, insulindosages, A1c levels, diet and exercise. Currently, much of thisinformation is collected from the patient via telephone which isproblematic (i.e., expensive, inconvenient and inaccurate). Otherstakeholders in DM can be mail order companies providing DM suppliessuch as test strips to patients and caregivers. As described below, mailorder companies currently exist that mail a maximum number of teststrips allowed to patients each month by Medicare or other third partypayors. This practice of mailing strips leads to unfair billing sincemany of these strips are unused or used ineffectively. The presentinvention provides benefits to each of these stakeholders andparticularly to disease management companies, healthcare networks andproviders, insurers and Centers for Medicare and Medicaid Services(CMSs), whose needs are often not emphasized as technological advancesin diabetes management are developed.

FIG. 1 illustrates some of the devices (e.g., BGM 18 and insulindelivery device 20) that can be used by a patient 12 or his or hercaregiver 34 to collect DM-related data and information. FIG. 3illustrates additional patient devices and some of the stakeholderdevices that can be used to connect to a repository 50 for diabetes dataand information and communicate with patient devices in accordance withan exemplary embodiment of the present invention. The patient devicescan include, but are not limited to, BGMs, insulin delivery devices,position tracking devices, nutrition and other data or information inputdevices. BGMs can be, but are not limited to, non-continuous BGMs (i.e.,BGMs that require a patient to draw blood for use as a sample on a teststrip that is then inserted into and read by a meter), or continuousmonitors (i.e., monitors using a catheter inserted under the skin totake fluid measurements for BG level). Insulin delivery devices can besyringes, insulin pens, insulin jet injectors, external insulin pumps,and implantable insulin pumps. Position tracking devices can be, but arenot limited to, pedometers and GPS tracking devices. Other devices forautomating DM-related data delivery from the patient 12 to otherstakeholders can be smart bottles for test strips, and wirelesssyringes, as described in more detail below. Other examples of patientinformation can be recording of activities such as diet, exercise andlifestyle (when meals are taken, exercise occurs, etc). A WiMax dockingstation or a cell phone can have a display and be programmed to generatea dialog screen to request input of food intake after a noon-timereading. A GPS tracking device can indicate when patient is at home orthe gym and generate a screen to enter exercise information. Similarly,a pedometer can monitor general exercise level via recorded movement.

FIG. 4 illustrates a repository 50 in accordance with an exemplaryembodiment of the present invention, and types of data and informationstored therein. For example, the repository 50 can store data 64 and 70from BGMs and insulin delivery devices, lifestyle information 74 such asmeal-times and food intake, exercise, patient location, medical datasuch as cholesterol, blood pressure, information 76 pertaining to numberof and lot number of test strips allotted to patient, testing frequencyand BG level goals and variances, meter/strip calibration data, and soon. The repository 50 also stores for each patient biographical data 60,including one or more recognized patient identifiers as described below,medical data and vital statistics 66, physicians orders. Appointment andprescriptions 72, among other information. The repository 50 can alsocontain analytical algorithms 78 for analyzing data stored therein and areport generation module 80.

With continued reference to FIG. 3, a wireless blood glucose meter (BGM)44 comprising a BGM 46 radio frequency (RF) communications circuit 48can communicate with various data users 60 (e.g., the patient wirelesscommunication devices such as PDA or laptop or PC, physician and othermembers of the patient's healthcare team and the disease managementcompany hired to work with patient) via various RF communicationspathways 52 in accordance with an exemplary embodiment of the presentinvention. FIGS. 5-17 illustrate different types of wireless. BGMs ordevices 44 containing BGMs and their respective communications pathwaysto the different data and information users. These devices cancommunicate with the data and information users and repository 50 via acellular network 54 and/or the internet directly 56 via one or moredevices 58 such as a cellular phone, personal data assistant (PDA),docking station, personal computer CPs or other computing device withcommunications capability. The RF technologies illustrated in thesefigures include, but are not limited to, cellular, Bluetooth, WirelessUSB, WiMax, WiFi and ZigBee.

With reference to FIGS. 5A and 5B, an exemplary wireless BGM 44 is shownas constructed in accordance with an illustrative embodiment of thepresent invention. The wireless BGM 44 includes a display 84 to showblood glucose level, date and 86 time the level was measured, alongother information. The wireless BGM has an antenna 86, a test stripreader input 88 and an on/off button 90. FIG. 5B illustrates a port 92for connecting the wireless meter to another device such as a dockingstation, cellular modem, and so on.

FIG. 6 illustrates components of an exemplary wireless BGM 44 asconstructed in accordance with an illustrative embodiment of the presentinvention. The wireless BGM 44 comprises a processor 96, a memory device98, a display 108 an input device (e.g., keypad 100), a test reader 102,a communications interface circuit 104, antenna 106 and power supply110. The test reader can comprise an analog front end 112, that is, atest strip interface between a strip port 114 and a processor 96 forglucose measurement. As described below, a BGM can be provided thatoperates with a base station, as shown in FIG. 11A, and therefore doesnot need an antenna 106. A communications interface circuit 104 can beconfigured to allow the wireless BGM 44 to communicate with one or morewireless protocols illustrated in FIG. 4, among others. If thecommunications interface circuit 104 enables the wireless BGM 44 tocommunicate via more than one wireless protocol, it can include ascanning device to scan the wireless frequencies available and toselect, based on optimal transmission qualities, the best communicationsprotocol to use to transfer data such as the most recent blood glucosereading to the repository.

In accordance with a preferred embodiment of the present invention, thewireless BGM 44 requires no user involvement to transmit blood glucosereadings following a test to the repository 50. For example, thewireless blood glucose meter 44 can be programmed and configured to bean event-driven device that automatically sends recently acquired testdata from the reader based on detection of insertion of the strip intothe reader, telephone activation if the wireless BGM is built into orconnected to a cellular telephone, pressure activation or selectedmotion activation of the wireless BGM. An embedded acknowledgementfunction is preferably implemented to ensure that the repository 50received the results completely (i.e., any errors in the transmitteddata can be sufficiently corrected or the data is retransmitted).

The wireless connectivity of the blood glucose meter 44 to therepository 50 and the automated transfer of blood glucose test resultsvia the wireless RF communications pathway facilitate increasedcompliance of the patient with diabetes management guidelines. This isbecause the test results are automatically provided to diabetesmanagement stakeholders. Further, the repository data is morecomprehensive since the automated delivery of the test results obviatessituations where patients or the caregivers fail to test and/or fail toreport the test results to the requisite stakeholders. Also, thecommunication of the data to a repository allows a level of abstractionand analysis of the data to provide other information (e.g., data on thenumber of tests performed could be used to facilitate test stripprescription tracking and replenishment; data on insulin delivery couldbe used to facilitate prescription tracking and replenishment ofsupplies.) In addition, as described above, other disease managementinformation can be transferred to the repository 50 and therefore to therequisite stakeholders via the same radio frequency communicationspathways such as GPS and pedometer readings, insulin deliveryinformation and meal-time information. These devices can be connected tothe blood glucose meter 46 and/or its RF circuit 48, or have a separateRF circuit, for communicating this additional information to therepository. Accordingly, unlike present blood glucose readers andcommunications interfaces such as patients' PCs, data such as bloodglucose test results and insulin intake and other disease managementinformation is given a wider view. In other words, the diabetesmanagement data and other information are available to morestakeholders, and the stakeholders have access to more comprehensiveinformation relating to the patient. By contrast, conventional devicesgenerally only give selected test results to selected persons who haveonly a local view of the test result information and no control overcompliance of the patient in testing or reporting the test results.Further, conventional blood glucose meters and other data devicesgenerally use separate communications transactions to send these resultsto the various persons involved, and generally do not employ arepository for the test results or other information.

In addition, the present invention allows for transfer of informationfrom patients 12 and other stakeholders (e.g., 14, 16, 40 and 42) to therepository and from the repository to patients and to other stakeholdersis preferably or ideally in real-time (e.g., immediately following ablood glucose test or insulin injection). It is to be understood,however, that the transfer of data between the stakeholders and therepository 50 can be configured to occur within a selected time periodfollowing an event (e.g., patient test, or repository algorithmicdetermination that a patient should receive a selected message), or aselected number of times per day, and so on.

FIG. 4 is a block diagram of an exemplary repository 50 in accordancewith an exemplary embodiment of the present invention. The repositorypreferably comprises many records 62 ₁, . . . 62 _(n) for respectivepatients 12 such as data transmitted from wireless meters and syringesor pens, data received via traditional means such being collected as theresult of telephone calls between two or more of a physician, diseasemanagement representative, insurer, and the patient, informationcollected from GPS devices, pedometers and meal-time information. Aswill be described in greater detail below, an illustrative embodiment ofthe present invention allows for test strip use, lot numbers,calibration data and meter number to be maintained for each patient 12.The organization of the data and information and identification of samewith respect to a particular patient 12 can be accomplished in a numberof different ways. For example, data received from a communications chipconfigured for use with the repository 50 can be sent packetized with aheader including a unique identification number assigned to a device 44or 58 as well as a patient 12. Data and information relating to aparticular patient 12 can be related to that patient via more than oneidentification means. For example, wireless meter 44 data can use aidentification code which can be a randomly generated code, and teststrip information can be related to the patient 12 and become a part ofthe patient's repository records based on a recognized patient IDassigned by Medicare, insurer or other payor, for example.

Returning to the wireless blood glucose meters of FIGS. 5, 7, 8, 9, 10Aand 10B, these devices referred to generally as 44 illustrate differentRF communication pathways between the wireless blood glucose meter andthe repository 50.

FIG. 7 illustrates a blood glucose meter 44 having a communicationscircuit configured to communicate with a device 58 such as a PCindicated generally as 58 a via wireless USB technology. The PC 58 a, inturn, can communicate with the repository 50 via the internet 56 or acellular network 54. In other words, the PC 58 a can be connected, forexample, to the internet 56 via an analog or digital connection orconnected to a cellular network 54 via a cellular modem card.

FIG. 8 illustrates a blood glucose meter 44 with the communicationsinterface circuit 104 having a built-in WiFi or WiMax communicationscapability for automated data transmission to a router or hub forproviding meter data to the repository via the internet.

FIG. 9 illustrates a blood glucose meter 44 with the communicationsinterface 104 circuit having a built-in Bluetooth or ZigBeecommunications capability for automated data transmission to therepository 50 via a user device 58 c such as a cell phone, PDA, and thelike, via the internet 56 and/or a cellular network 54.

FIGS. 10A and 10B illustrate a blood glucose meter 44 that communicateswith the repository 50 via a cellular network 54. As shown in FIG. 10A,the blood glucose meter 44 can have a cellular communications chip builtinto it as the communications interface circuit 104. Alternatively, theblood glucose meter can be provided with the cellular modem attachment120, as shown in FIG. 10B.

In accordance with the another exemplary embodiment of the presentinvention, a blood glucose meter 44 can be configured for use with adocking station 124, as shown in FIGS. 11A, 11B and 11C, in lieu ofhaving a communications interface circuit 104 and antenna 106 asdescribed above in connection with FIG. 5A. The docking station 124comprises a cradle 126 for receiving the blood glucose monitor 44, adisplay 128, and a number of user buttons or controls indicatedgenerally at 130. The buttons indicated at 130 comprise, but are notlimited to, a button for contacting specified persons such as aphysician, a button for reviewing reminders sent to the docking stationfrom the repository in accordance with instructions from a diseasemanagement representative or physician, a button for displaying menuoptions on the display 128, an emergency button for one-touch dialing ofan emergency number such as 911, and a button for indicating quick factson the display regarding diabetes management. Among the menu options isa send option to send recent blood glucose test results to therepository 50 when the meter 44 is in the cradle 126. With referencewith FIGS. 11D and 11E, the portable meter 44 has a display 84, a teststrip input 88, and on/off button 90 and a port 92 for connecting to acorresponding connector in the cradle 126.

With reference to FIG. 11F, the docking station 124 comprises aprogrammable processor 132, a display 128, a memory device 134, aconnector 136 for electrically communicating with the meter when themeter is inserted in the cradle, a number of buttons and other userinput devices 130, a communications interface 140 to the repository viathe internet or a wireless network and a power supply 138. The meter 44has a test strip reader 114, a processor 96, a memory 98, a display 108and on/off button 90 or other user input device, and a connector (notshown) for electrically communicating with the docking station when themeter is inserted in the cradle.

As shown in FIGS. 12A and 1213, when the blood glucose meter 44 isdocked in the docking station 24, the docking station can communicatevia wireless technology such as Bluetooth to a device 58 such a cellularphone or PDA which, in turn, communicates with the repository 50 via awireless network or the internet. Alternatively, the docking station 124can be provided with the cellular modem such that, when the meter 44 isin the docking station cradle 124, the docking station 124 can transmittest results to the repository 50 via the cellular network.

FIGS. 13-16 illustrate other types of devices having a blood glucosemeter and radio frequency connectivity to the repository.

FIGS. 13A, 13B and 13C illustrate a cellular telephone 142 having abuilt-in test strip reader 144 and display 146 similar to that of theblood glucose reader described above in connection with FIGS. 11B and11C.

As shown in FIG. 14, a cellular telephone 148 can have automatic datatransmission connectivity to the data repository 50 via the cellularnetwork. FIG. 14 illustrates a cell phone 148 with a BGM attachment 150.

FIGS. 15A through 15D are various views of an insulin delivery device160 such as a syringe that is provided with an RFID tag for transmittinginformation such as syringe identification number, and data stored in anon-volatile EEPROM in the tag such as insulin-type delivered by thesyringe, amount, insulin type, and so on. The amount can be detected andstored based on plunger motion. Accordingly, when a glucose meter 44 isproximal to the syringe 160 to create a sufficient electromagneticfield, the RFID in the syringe can be activated to send the datarelating to the insulin dose delivered by the syringe.

FIG. 15A is a perspective view of the syringe 160 having a cap 162 onthe needle. FIG. 15B is a perspective view of the syringe 160 having thecap 164 at the top of the reservoir 166 for the insulin removed. The topof the reservoir can be configured with the RFID tag, the plunger andthe plunger motion sensor. FIGS. 15C and 15D are front and side elevatedviews of a syringe 160 having the reservoir cap 164 removed.

FIGS. 16A through 16E are various views of another insulin deliverydevice 170, that is, an insulin pen having RF connectivity in accordancewith an exemplary embodiment of the present invention. FIGS. 16A and 16Bare perspective views of the pen 170 with the cap 172 on. FIG. 16C is aperspective view of the pen 170 with the cap 172 removed and the insulindelivery mechanism exposed. FIGS. 16D and 16E are top and side elevatedviews of the insulin delivery pen with the cap on.

As indicated in FIGS. 16B, 16C and 16D, the insulin delivery pen 170 hasa display 174 for indicating insulin dose and other information such asmix amount, time and date of insulin delivery. The pen 170 is providedwith a communication circuit (not shown) for communicating the data tothe repository using one of the RF communication pathways describedabove in connection with the blood glucose meter 44.

The exemplary insulin delivery devices shown in FIGS. 15A-15D and FIGS.16A-16E require no patient or caregiver involvement to communicate theinsulin delivery data to the repository. The connected syringe data canbe sent when the meter data is sent and basically coincides with bloodglucose testing. The connected pen data can be automatically transmittedto the repository 50 upon detection of complete insulin delivery. Asshown in FIG. 17, the insulin delivery data can therefore be sent using,for example, the wireless transmission methods described above inconnection with FIGS. 4 through 10. Other injection devices can include,but are not limited to, microneedle delivery, external and implantedinsulin pumps with or without PC interfaces. With further reference toFIG. 17, a meter 44 can therefore be configured to communicate with apump, for example, via a local network and with the repository 50 via awide network. In accordance with the exemplary embodiment of the presentinvention, the pens 170 are configured to store multiple doseinformation which can be transmitted automatically to the repository.

Exemplary embodiments of the present invention allow for reactive andreal-time management of diabetes management data and information bydiabetes management stakeholders, in particular stakeholders such asdisease management companies, insurers, healthcare networks andemployers whose functions have not, in the past, been optimized. Asstated above, the automatic transmission of blood glucose meter data andinsulin delivery device data to a repository 50, and the use of therepository 50 to also collect, store and access diabetes managementinformation such as food intake and exercise and other health parameterssuch as blood pressure and cholesterol, allow for increased patientcompliance and more comprehensive information for review by diseasemanagement case workers, physicians, insurers, and other diabetesmanagement stakeholders. DMCs, in particular, benefit from the real-timeand comprehensive information and data provided to the repository 50 inaccordance with an exemplary embodiment of the present invention. In thepast, problems commonly experienced by disease management companiesincluded lack of real-time data access (i.e., because much of the datawas collected via telephone conversations between representative andpatients), insufficient physician involvement, inability to scaleoperations cost-effectively and therefore costly case management. Anumber of improved disease management operations will now be describedwith reference to FIGS. 18A and 18B and in accordance with exemplaryembodiments of the present invention.

Referring to FIGS. 18A and 18B, disease management companies can nowreview (block 180) the various records available for selected patientsin the repository 50 and determine when blood glucose test results andother test results such as A1c testing are outside selected parametersfor respective patients based on variations in a patient's blood glucoselevels and other test results. The disease management company canprioritize which patients need to be contacted by a representative andprovided with additional educational information (blocks 182 and 184).For example, an algorithm at the repository can use parameters specifiedby a stakeholder to determine those patients whose test results indicatethat prompt attention or intervention is needed. A report generatingmodule at the repository 50 allows for exception reporting, that is,selection of patients whose parameters meet selected criteria and needan alert message to be sent via the two-way wireless pathway of thepresent invention, or simply generation of an exception report (blocks208 and 210). Thus, a stakeholder can use the reports generating abilityof the repository 50 to know how many hypoglycemic events occurred amongtheir patients in a given time period. In addition, a disease managementcompany can also improve the assignment of cases among diseasemanagement representatives to facilitate their case load management. Inaddition, variations among a patient's blood glucose data, as well asmeal-time habits and other stored information, can be analyzed to allowthe data management company to customize the frequency with which apatient tests blood glucose levels and performs other tests such as A1ctesting (blocks 186 and 188). Users can then be sent reminders via thebase station or the display on wireless blood glucose meters regardingwhen to test, if a particular test has been overlooked by the patient,or alerts when levels are outside a selected range (blocks 190 and 196).Alerts can be custom or generic alerts in accordance with an aspect withthe present invention.

With continued reference to FIGS. 18A and 18B, stakeholders can use therepository and two-way radio frequency communications between themselvesand patients (i.e., via meters, docking stations, cellular phones,computers, PDAs or other devices) via the communication pathwaysillustrated in FIG. 4 or other networks such as the public switchtelephone network (PSTN). The two-way communications provided by thepresent invention between the patient and other diabetes managementstakeholders allows determining drug therapy compliance (block 196)through the analysis of repository 50 data relating to test strip useverification and insulin doses administered (block 198), as well as forthe confirmation (block 194 and 200) of receipt of an alert sent to thepatient (e.g., when a test blood has expired or is defective, when testblood glucose levels are outside a selected range, and so on) (blocks192 and 206). The repository 50 can comprise different test data such asA1c and glycosylated serum protein test data for analysis by astakeholder for short-term, mid-term and long-term evaluation of bloodglucose levels and prediction of events for a specific patient such asblood glucose levels falling outside a desired range (block 202 and204). The repository 50 allows for generation of a greater variety ofreports since the data is more comprehensive. For example, diseasemanagement companies can perform compliance reporting for selected onesof groups of patients (diabetes patient population trends reports), andreal-time exception reporting. Reports can be generated for differentstakeholders (e.g., patient, case manager and healthcare provider) thatare linked but also have unique portal space in the repository such thatnotes can be posted and responded to among the stakeholders. Also,reports can be represented differently on the respective stakeholders'computer screens to have varying information and functional features,depending on the stakeholder viewing the report.

Thus, the exemplary embodiment of the present invention providesstakeholders with a means to move from reactive disease management toreal-time and proactive disease management and therefore provide suchdirect benefits as increased productively for case workers andreductions in management cost and time expended, improved clinicaloutcomes, increased patient care and satisfaction (e.g., due to thereal-time aspect of viewing and responding to test data), and greaterhealthcare team involvement. These benefits lead to such secondarybenefits to DMCs as increased patient enrollment and businessopportunities. Insurers, for example, can better evaluate financialimpact of a disease management program based on outcomes and trendsreports that can be obtained from the repository 50 described above inaccordance with an exemplary embodiment of the present invention, andreceive better cost effectiveness from a contracted disease managementcompany. Using one or more of the exemplary embodiments of the presentinvention described herein, healthcare networks can increaseproductivity by spending less time gathering data and more timeproviding care to patients. Repository 50 data can be made available tomultiple hospital and clinic sites. Patients are more satisfied whenhealthcare networks enroll in a system in accordance with an exemplaryembodiment of the present invention because patient data is availableanytime and wherever the patient goes, prescriptions are automated andpatient data is securely available to the right people involved with apatient's disease management.

The exemplary embodiment of the present invention also allows diseasemanagement companies and other stakeholders to monitor drug therapycompliance. For example, diabetes management stakeholders can reviewmedication dosages reported automatically, as well as collectedinformation in the repository regarding test strip lot and correspondingtest results and determine if a patient is maintaining aphysician-directed schedule for testing and otherwise managing bloodglucose levels. As described above, alerts can be sent when bloodglucose levels are outside a selected range or test strips have expiredor otherwise need to be replaced. As will be described below inconnection with FIG. 19, tracking of test strip use in accordance withan exemplary embodiment of the present invention allows for moreeffective use of test strips, better control over test strip quality andquantity delivered to patients and more efficient billing to Medicare.

The automated transmission of blood glucose results and test strip lotnumber and meter calibration data allows for stakeholders with theaccess to the repository 50 to determine those test strips that haveactually been used. Currently, Medicare guidelines determine the numberof test strips that are sent per month to diabetes patients. Currently,there is no way to track whether the test strips are actually used. Mailorder companies are permitted to bill Medicare for the maximum amount oftest strips allotted to a patient regardless of whether the test stripsgo largely unused by the patient. Mail order companies need only contactthe patient once each month before sending the Medicare-directed numberof test strips to that individual and then billing Medicare for thosestrips. Accordingly, a significant amount of test strips paid for byMedicare can go unused and without any method of detecting the magnitudeof such waste.

With reference to FIG. 19, an exemplary embodiment of the presentinvention resolves this problem through the automatic transmission oftest results from meters (e.g., meters 44, 142 or 148) to the repository50 without any user interaction or interference. The repository 50 canbe configured to store the number of test strips allotted by Medicare,to a patient, the number of recommended tests per day the patient is toundergo, the number test results that have been received, and determinehow many unused test strips a user has within a particular month (blocks222 and 240). Based on this information, it can be determined whether auser needs a refill of test strips. Billing can therefore be on thebasis of number of test strips that have actually been used,representing a significant savings to Medicare and other payors overcurrent wasteful practices. The repository 50 and the automatedcommunications described herein in accordance with exemplary embodimentsof the present invention also allow for determination of refills andautomated fulfillment of same since the number of unused test stripsthat are left can be determined (blocks 226 and 228). A vendor can usethese automated communications and the repository 50 to estimate when apatient is going to be out of test strips and can automatically sendmore when the patient has only, for example, a two week supply leftAlternatively, a vendor can be sent a message to send no more refillsuntil a prescribed number of test results are received (block 240).

With continued reference to FIG. 19, the repository 50 also allows forreview of testing practices and blood glucose results and can sendpromotional material from pharmacies or pharmaceutical companies toselected patients. As described above, the connected blood glucose meter(e.g., an RF meter 44 or a cell phone meter 142 or 148) provides forability to send not only messages from the patient's healthcare team, oreducational content to the patient, but also other types of messages.For example, as part of a business model in accordance with an exemplaryembodiment of the present invention, advertising can be sold tocompanies who have targeted messages that they want these patients toreceive (blocks 230 and 232). For illustrative purposes, apharmaceutical company that is introducing a new diabetes therapy cantherefore buy an advertisement that is transmitted to those patientswhose health profile fits a potential target for the new therapy. Theseprofiles can be obtained using algorithms and report generationoperations of the repository 50.

In addition, as indicated in FIG. 19, overall accuracy of test stripsand meters can be monitored by reviewing blood glucose levels, test triplot numbers and meter calibration information (block 238). Finally, iftest results are consistently outside desired parameters or nonexistent,alerts can be sent in the event that the test strips are defective orthe meter 44, 142 or 148 is malfunctioning (blocks 234, 236 and 238).Accordingly, vendors can be advised to send replacement strips formalfunctioning or expired tests strips. Thus, automated test resultsreporting and management of other data such as test strip lot numbersand patient data such as recommended frequency of testing and thereforetest strip usage tracking presents many advantages over current diabetesmanagement systems such as tracking of expired or defective test strips,eliminating abusive practices such as test strip hoarding and unfairbilling to Medicare or Medicaid, and monitoring associations betweentest strips and meters, to name a few.

Currently, Medicare requires mail order companies to call and askpatients if they need more test strips before sending them. Mail ordercompanies can avoid the time and expense of making such calls since thenumber of test strips actually used can be tracked using theconnectivity and repository of the present invention. Further, DMCs findthe hiring of staff nurses to manage case loads to be difficult andexpensive. The device connectivity and repository 50 described herein inaccordance with exemplary embodiments of the present invention, however,can provide patients with a virtual coach and reduce reliance on nursesand other case managers. Using algorithms at the patient device 44, 142or 148 or in the repository 50, the collected and stored data andinformation at the repository 50 and the two-way communication functiondescribed herein, points of education can be generated and sent viamessage to the patient as needed to improve medical outcomes.

The exemplary embodiments of the present invention also allow fordifferent and advantageous programs to be implemented. For example, withreference to FIG. 20, a cellular network-based system can be implementedwherein a monthly subscription fee can be determined based on testfrequency and the number of times test data is uploaded to therepository (block 250). Once monthly subscribers are enrolled, they canbe provided with blood glucose meters and test strips at no cost or atnominal cost, obviating the above-mentioned abusive practices of billingMedicare for unused strips (block 252). As the test data for aparticular subscriber is uploaded, it can be reviewed to determine ifmore strips are needed (blocks 254, 256, 258 and 260). Also, patients'overall ability to manage the blood glucose within desired ranges can bedetermined and cash-back incentives or other promotional items can beprovided to physicians and/or patients exhibiting improved diabetesmanagement through their improved comprehensive test results (blocks 262and 264). In addition, the third party payor (e.g., Medicare) would onlypay for those test strips that had an associated result in the datarepository 50 thereby reducing the likelihood of fraud and abuse in thesystem of reimbursement for diabetes supplies.

In accordance with an aspect of the present invention, radio frequencyidentification (RFid) technology is employed to realize advantages overexisting disease management devices. The term “radio frequencyidentification transponder” is used to refer to any of a class ofcompact radio receiver-transmitters that are powered by an ambient radiofrequency field. The transponder is accessed by modulating the fieldwith an appropriate communication signal. The reaction can be aresponsive signal, a change in the transponder, or both. The content ofthe communication signal and the response of the transponder are limitedby the memory and control functions provided by the transponder and bythe access time bandwidth available for communication. Within thoselimits, the transponder can be read and written in a manner similar toother digital memory devices used to store and retrieve digitalinformation. Radio frequency identification transponders are widelyavailable in a variety of forms. These devices include a non-volatilememory, such as an Electrically Erasable Programmable Read-Only Memory(EEPROM) semiconductor component integrally contained in thetransponder. Stored in the nonvolatile memory are encoded data. Theradio frequency identification transponder also contains an antenna. Theshape of the transponder and the antenna can vary depending on thespecific embodiment. Memory and any control functions are provided bychip mounted on the support and operatively connected through the leadsto the antenna.

In accordance with an exemplary embodiment of the present invention, ablood glucose monitor 270 is provided which has a body 272, a glucosesensor (not shown) mounted in the body, a display 274, a radio frequencyidentification transceiver 276, and at least one radio frequencyidentification transponder 278 mounted within the body, as shown inFIGS. 21A and 21B. The transceiver 276 and transponder 278 areunshielded by the body. The lines 290 represent an ambient-frequencyfield generated by the transceiver 276.

During use, a container 280 of test strips including a radio frequencyidentification transponder 282 (e.g., integrated into a container label284 or the lid 286 as shown in FIGS. 22 and 23, respectively) orindividual test strips 288 containing a radio frequency identificationtransponder (FIG. 24) have their radio frequency identificationtransponders 282 activated by the blood glucose monitor's transceiver276, as indicated by the line pattern 290 in FIG. 25. This results inthe container 280 of test strips, or the individual test strip 288,transmitting data comprising an encodement (indicated by line pattern292) necessary for the monitor 270 to calculate an accurate measure ofthe blood glucose level in the blood sample applied to the test strip288.

This exemplary embodiment of the present invention realizes a number ofadvantages and improvements over the existing diabetes managementdevices. The typical use of a conventional blood glucose monitorrequires that the user manually enter a code number into the bloodglucose monitor that corresponds to the code number printed by themanufacturer on the test strip container. This code number is a type ofcalibration data that ensures that the results obtained are accurate tothe degree claimed by the manufacturer in the labeling for the teststrips. If the user of the blood glucose monitor does not pay attentionto this code number or enters an incorrect code number, the bloodglucose results obtained could be significantly different than theresults obtained with a correct code number. A significantly higher orlower result could lead to incorrect medical therapy by the user or thehealthcare professional performing the blood glucose test. By contrast,having the encodement 292 transmitted from the test strip container orthe individual test strip in accordance with the exemplary embodiment ofthe present invention ensures that the blood glucose test provides themost accurate result, eliminating the likelihood of an inaccurate resultdue to user error. Also, the encodement can contain additionalinformation such as, for example, date of manufacture, the test stripexpiration date, lot number, manufacturer identification, and logisticinformation such as distribution country or region. This additionalinformation can be stored in the repository 50 and used by the system ofthe present invention, which is exemplified by the illustrativeembodiments disclosed herein, to provide alerts or warnings about theexpiration date, to enable or disable use of certain combinations ofmeters and test strips depending on the country or region, and to aidlogistics management.

The present invention, which is exemplified by the illustrativeembodiments disclosed herein, provides solutions to prior art problems.When the blood glucose test strips are manufactured and a calibrationcode is established for a particular lot, this code is embedded in theradio frequency identification transponder 282 of either the container280 holding these test strips, the individual test strips 288, or both.When a container 280 of test strips or an individual test strip 288 isin close proximity to the blood glucose monitor 270, the blood glucosemonitor's transceiver 276 creates a field 290 that activates thecontainer or test strip radio frequency identification transponder 282which then automatically transmits its embedded code 292 to the bloodglucose monitor 270. The blood glucose monitor 270 then uses this codein calculating the blood glucose result that is displayed once a teststrip with a blood sample has been received in the blood glucosemonitor. Further, the encodements 292 can include information about theindividual test, whether from the transponder in the container, thetransponder in the test strip, or the transponder contained within themonitor itself. Examples will now be described.

In a first example, two elements contain radio frequency identificationtransponders, that is, the blood glucose monitor 270 and the test stripcontainer 280. In this example, the close proximity of the test stripcontainer to the blood glucose monitor is required for the monitor toreceive the calibration code.

In a second example, two elements contain radio frequency identificationtransponders, that is, the blood glucose monitor 272 and the individualtest strips 288. In this example, the close proximity of the test stripdue to its insertion in the blood glucose monitor is required for themonitor to receive the calibration code.

In a third example, three elements contain radio frequencyidentification transponders, that is, the blood glucose monitor 270, thetest strip container 280, and the individual test strips 288. In thisexample, the close proximity of both the test strip container and theindividual test strip are used as a confirmation by the blood glucosemonitor that the inserted test strip has the same calibration code asthat transmitted by the test strip container.

In a fourth example, the test strip container 280 stores and transmitsthe calibration code, the test strip expiration date, and the lotnumber. These data are interpreted by the meter 270 by comparing thetest strip expiration date to the current date set in the meter todetermine if the test strip 288 being used has expired or not.

In a fifth example, the test strip 288 stores and transmits thecalibration code, the test strip expiration date, and the lot number.These data are interpreted by the meter 270 by comparing the test stripexpiration date to the current date set in the meter to determine if thetest strip being used has expired or not.

In a sixth example, the radio frequency identification transponder 278in the blood glucose monitor 270 is used for communication with otherdevices such as a pump or docking station or detector in warehouse ormanufacturing location. In other words, a pump or docking station cantransmit a field via a transceiver to determine if a BGM 270 islistening and can communicate with it. A detector can transmit a fieldthat activates the radio frequency identification transponders of theblood glucose monitors packed in a crate to determine if any of themwere incorrectly packed and therefore to avoid shipping errors.

In accordance with an exemplary embodiment of the present invention, ameans for automatically determining the association of a diagnostic testperformed by an individual to a mealtime is provided. The association ofa diagnostic test to a mealtime is based on the timing of a therapeuticintervention performed by the individual. The present invention isdirected to both an analytical process and the parameters used by theanalytical process. The present invention is exemplified whendetermining, for a given blood glucose test, whether that test is takenprior to a meal or after a meal based on the timing of an associatedinsulin injection. Described below are two methods, that is aparameter-based method (FIG. 26) and an analytical method (FIG. 27), forautomatically making this determination in accordance with exemplaryembodiments of the present invention.

In the parameter-based method (FIG. 26), the determination relies ontherapy data (e.g., insulin injections) as indicated by block 300 anddiagnostic test data (e.g., blood glucose meter test results) asindicated by block 302 and their corresponding time stamps, as well as aset of parameters (block 304) provided by the individual as follows:

A single time representing the latest an individual would eat theirfirst meal (M1);

A single time representing the latest an individual would eat theirsecond meal (M2);

A single time representing the latest an individual would eat theirthird meal (M3);

A single time representing the latest an individual would go to sleep(S1); and

A single time representing the latest an individual would test theirblood glucose in the middle of the night. (N1).

In the parameter-based method, the determination also relies on a set oftiming thresholds internal to the analysis as follows:

blood glucose test times that are less than or equal to 30 minutesbefore the injection time are categorized as before the meal (blocks 310and 312);

blood glucose test times that are greater than or equal to 90 minutesAND less than or equal to 180 minutes after the injection time arecategorized as after the meal (blocks 314 and 320);

blood glucose test times that are less than or equal to 45 minutesbefore the injection time AND are greater than or equal to 180 minutesafter the previous injection time are categorized as before the meal(blocks 312 and 318); and

blood glucose test times that are greater than or equal to 30 minutesafter the injection time AND are less than or equal to 90 minutes afterthe injection time are categorized as unknown (blocks 316 and 322).

The allocation of values (block 308) in accordance with this exemplaryembodiment of the present invention is as follows:

if the injection time is before M1 on a given day, that injection willbe associated with the first meal of the day;

if the injection time is after M1 and before M2 on a given day, thatinjection will be associated with the second meal of the day;

if the injection time is after M2 and before M3 on a given day, thatinjection will be associated with the third meal of the day;

if the injection time is after M3 and before S1 on a given day, thatinjection will be associated with the bedtime for that day; and

if no injection time and the blood glucose test time is after N1 andbefore N1+5 on a given day, that blood glucose test will be associatedwith a nighttime test.

Contention between multiple tests is resolved in accordance with thisexemplary embodiment of the present invention as follows: if two bloodglucose tests are performed prior to an insulin injection, the bloodglucose test closest in time to the injection time is used for theanalysis. Based on these parameters, a data set of insulin injectiontimes and blood glucose test times can be analyzed to determine thefollowing, for example:

which blood glucose tests are associated with an injection; and

whether the blood glucose test is categorized as a before meal test oran after meal test for three mealtimes, a bedtime test, or a nighttimetest.

In the analysis-based method (FIG. 27), the determination relies onperforming an analysis of the individual's data to determine:

the number of injections for each day; and

the number of blood glucose tests for each day (block 330).

Additionally, the individual can provide a number representing thetypical number of meals eaten per day (block 332).

Insulin injection times and blood glucose test times are examined todetermine how the times cluster (block 334). This may be performed usingaverage times and some measure of variation and confidence intervalsaround those times throughout the day, relative to the number of mealseaten per day (block 336). This provides a means to segment the day intomealtimes, bedtime, and nighttime. Once the values are segmented, theanalysis proceeds as in the parameter-based method described above todetermine whether a blood glucose test is before a meal or after a mealusing the timing thresholds, that is:

blood glucose test times that are less than or equal to 30 minutesbefore the injection time are categorized as before the meal (blocks 310and 318);

blood glucose test times that are greater than or equal to 90 minutesAND less than or equal to 180 minutes after the injection time arecategorized as after the meal (blocks 314 and 320);

blood glucose test times that are less than or equal to 45 minutesbefore the injection time AND are greater than or equal to 180 minutesafter the previous injection time are categorized as before the meal(blocks 312 and 318); and

blood glucose test times that are greater than or equal to 30 minutesafter the injection time AND are less than or equal to 90 minutes afterthe injection time are categorized as unknown (blocks 316 and 322).

This aspect of the present invention realizes a number of advantages andimprovements over the prior art. In the past, the determination ofmealtimes was wholly dependent on one of two conventional methods:

1. An individual assigning fixed times to their before and after mealtime periods; and

2. An individual “marking” their data in such a way as to indicatewhether a test or action occurred before or after a meal, at bedtime, orin the night. In the first conventional method, a problem occurs in thatthe fixed times cannot take into account variations in daily life thatmight change the timing of meals, bedtime, or a middle of the nightevent. As a result, data that are from a time period after a meal aremisrepresented as having occurred before a meal and vice versa. In theconventional second method, a burden is placed on the individual to makean extra effort to categorize each event either for later analysis orretrospectively “marking” each value according to its category. It isunlikely that an individual will either spend the time to mark everyevent, or that they will remember to mark every event at the time itoccurs. Further, if they perform the “marking” retrospectively, theaccuracy of their recollection is diminished, thus diminishing theaccuracy of the event allocation.

The exemplary embodiments of the present invention described inconnection with FIGS. 26 and 27 solve problems encountered with theseconventional methods. First, these embodiments use the timing of atherapy intervention that is typically associated with the periodimmediately before a meal or immediately before bedtime and uses it'soccurrence as a proxy for the mealtime or bedtime. Thus, the accuracy ofthese embodiments of the present invention are directly related to theaccuracy of the time information for the therapy intervention.Accordingly, if the therapy intervention's timestamp is itself automatedand more accurately determined, the manner by which these embodimentscorrectly categorize the diagnostic test's timing is improved. Secondly,these embodiments establish timing thresholds that provide the abilityto determine the most likely physiologic relationship between thetherapy intervention and the diagnostic test.

With reference to FIG. 28, a variation of the analysis-based embodimentdescribed above is used with an analytic engine that contains aniterative learning algorithm that uses feedback from the individual toimprove the accuracy of the categorizations over time. That is, with theinitial dataset from an individual, the analytic engine can perform asdescribed above, but the individual can then provide feedback in theform of corrections or changes to the categories defined by the engine(block 340). The analytic engine then incorporates this feedback intoits algorithm and, on successive analyses, requires fewer corrections(block 342).

The underlying technical principle of this aspect of the presentinvention is a series of date and time comparisons that are performed ona dataset comprising two categories of values, where each value in eachcategory has a unique date and time stamp. The first part of theapproach compares the dates and times of the two categories of data tofind close associations in time between data points. The second part ofthe approach is dependent on whether a parameter-based method (FIG. 26)is used or an analysis-based method (FIG. 27) is used. In generalthough, this part makes the assignment to categories of before or aftermeal, bedtime, or nighttime according to external parameters or to astatistical analysis of the dataset.

Fundamental to both methods of FIGS. 26 and 27 is the ability toestablish timing thresholds that link the two categories of data orvalues. These timing thresholds would be based on clinical experienceand physiologic data, or based on an analysis of an individual datasetover time. A related aspect of the present invention is the improvementin accuracy as the therapy intervention's date and timestamp accuracyimproves, particularly if the therapy intervention's date and timestampis automatically determined and stored in the dataset. The dataset(e.g., the two categories of data, and their associations in time), andthe algorithm(s) for implementing the parameter-based or analysis-basedmethods, can be provided in repository or within the devices themselves.Placing the dataset and algorithm(s) in the repository 50 simplifies thedevice and realizes the advantages discussed above (e.g., reduceddevelopment time and therefore time to market, reduced complexity andtherefore reduced potential for safety hazards, increased useable lifeof the device). In any event, the data in the repository 50 or withinthe devices themselves (e.g., meter 44) can be analyzed to abstractinformation about the patient's behaviors. This analysis can realizeanother advantage of improved messaging. In other words, the repository50 can perform one or more algorithms to determine when messages such asalerts and educational messages should be sent to patients. A patient'stest results, insulin intake and mealtimes can be analyzed to determinean optimal time at which to send a reminder message to the patient totake a test or administer insulin or schedule a physician's officevisit, for example. Also, algorithmic processing of the repository 50contents can affect the determination of a patient's readiness andwillingness to receive information to that will optimally impact achange in that patient's behavior and his or her diabetes managementpractices.

Another benefit is that with a device (e.g., meter 44) that has an“always on” wireless connection, sophisticated firmware in the devicesis no longer needed for performing analytical operations. For example,many BGM devices today provide BG averages, or graphical trend data, andso on. With the kinds of systems described herein in accordance withexemplary embodiments of the present invention, the devices (e.g.,meters 44, 142 and 148) need not have any of these analyticalcapabilities, but rather merely act as display devices for the analyticsperformed at the repository level. In this way, the devices become lesscomplex, which provides a number of benefits (e.g., reduced developmenttime and therefore time to market; reduced complexity and thereforereduced potential for safety hazards, increased useable life of thedevice because software “upgrades” are performed at the repositorylevel, not at the device level so devices do not have to be replaced,the ability to perform device firmware upgrades wirelessly withoutrequiring the device to be replaced.

FIGS. 29-31 describe improved services and potential revenue benefitsrealized by the system of the present invention depicted in FIGS. 3 and4 and described herein as exemplified in FIGS. 5 a through 17. FIGS. 29,30 and 31 illustrate the benefits of the connectivity and value addedinformation provided by exemplary embodiments of the present inventionin the context of overall patient and disease management.

As shown in FIG. 29, the left side of hashed line demarcates currentmeasurement practices of different diagnostic data that is sharedbetween a patient, a healthcare provider and other parties as describedabove in the background section. The right side of hashed line indicatesadvantages of the exemplary embodiments of the present invention. Forexample, the effortless data capture and send operations of theconnected BGMs, continuous glucose monitors (CGMs) and insulin deliverydevices and the “information from data” services provided using therepository 50, as described herein in accordance with exemplaryembodiments of the present invention, provide integrated services forboth customers and businesses including, but not limited to, patients,caregivers, DMCs, healthcare providers, integrated health networks(IHNs), employers and insurance companies. In addition to diabetes, thepatient management and disease management services provided by theexemplary embodiments of the present invention are useful for differenttypes of healthcare conditions including, but not limited to, pulmonarycare, cardiac care, fitness/well-being care. Examples are provided inFIGS. 30 and 31 such as a diabetes nurse educator (DNE) trackinghundreds of patients through a repository portal and noting that certainpatients need immediate attention.

FIGS. 32-37 illustrate retail money flow advantages provided byexemplary embodiments of the present invention. For example, FIGS. 32and 33 each illustrate product flow such as test strips from a BGMmanufacturer to a patient via a wholesaler and retailer, and revenueflow between these parties. FIGS. 35 and 36 illustrate similar partiesexcept for a third party payer such as a managed care organization inlieu of Medicare. FIG. 37 also includes a pharmacy benefits manager(PBM). FIG. 34 illustrates product flow from a BGM manufacturer to apatient via a durable medical equipment supplier or DME, and revenueflow between these parties. The accurate test result reporting,proactive disease counseling, test strip tracking and other advantagesof the exemplary embodiments of the present invention provide theadditional benefit of significant cost savings and therefore can allowfor rebates as shown.

FIGS. 38, 39 and 40 illustrate improvement over current cash flowsbetween DM stakeholders afforded by a pay-for-results model implementedin accordance with an exemplary embodiment of the present invention suchas determining actual use of test strips. As shown in FIG. 38, a diseasemanagement company can determine from an order in the repository 50 thata patient should receive 50 test strips per month based on their currentprescribed testing frequency. A mail order or retail vendor can purchase50 strips from a BGM manufacturer and ship them to the patient and billthe DMC. The DMC and/or payor can, in turn, determine from therepository that only 46 test strips were used by the patient during aselected period of time as determined using the method described abovein accordance an exemplary embodiment of the present invention. Thepayor need only pay for 46 test strips. The DMC and/or payor can receivea rebate for the 4 unused test strips.

FIGS. 41A through 41D, 42 and 43 illustrate additional advantages of theconnected disease management devices and data capture and analysesmethods described herein with reference to exemplary embodiments of thepresent invention. FIG. 41D illustrates how the system illustrated inFIG. 3 collects data such as blood glucose level, date and time, amongother optional data such as pre-meal and post-meal readings. As shown inFIG. 41B, a user is given real-time feedback based on informationanalyzed in the repository 50 (e.g., ADA target or physician prescribedtarget values for blood glucose levels). As shown in FIG. 41C, the datain the repository can be used to calculate a required insulin dose orother medication that can be transmitted to the BGM to prompt users totake required medication level. With reference to FIG. 41D, the testingand dosage data, among other information such as nutrition and pre-mealor post-meal blood glucose levels, is stored in the repository 50 foruse by various stakeholders such as a patient, healthcare provider, DMCand so on. As shown in FIG. 42, the data can be collected, analyzed andsummarized in a display screen for a number of patients to moreeffectively manage diabetes patient populations. The display screen caninclude recent readings, averages over a selected number of days andinsulin dose compliance that is color coded or shaded to enhanceidentification of patients whose ranges or readings are high, low orwithin a target range. As show in FIG. 43, the data for a selectedpatient can be captured on a display screen as a one-page action planwith additional information such as blood glucose averages over time.

It is to be understood that the exemplary embodiments of the presentinvention described herein can be embodied as computer-readable codes ona computer-readable recording medium. The computer-readable recordingmedium is any data storage device that can store data which canthereafter be read by a computer system. Examples of thecomputer-readable recording medium include, but are not limited to,read-only memory (ROM), random-access memory (RAM), CD-ROMs, magnetictapes, floppy disks, optical data storage devices, and carrier waves(such as data transmission through the Internet via wired or wirelesstransmission paths). The computer-readable recording medium can also bedistributed over network-coupled computer systems so that thecomputer-readable code is stored and executed in a distributed fashion.Also, functional programs, codes, and code segments for accomplishingthe present invention can be easily construed as within the scope of theinvention by programmers skilled in the art to which the presentinvention pertains.

While certain exemplary embodiments of the invention have been shown anddescribed herein with reference to certain preferred embodimentsthereof, it will be understood by those skilled in the art that variouschanges in form and details may be made therein without departing fromthe spirit and scope of the invention as defined by the appended claimsand their equivalents.

1. A computer-implemented method of processing diagnostic datacomprising: receiving diabetes therapy delivery data and correspondingtime stamps for when different diabetes therapy delivery events wereadministered to a patient; receiving diagnostic diabetes test data andcorresponding time stamps for when diagnostic diabetes tests wereadministered to the patient; receiving values corresponding to thelatest time at which the patient would eat each of at least two meals;and analyzing, using the computer, the diabetes therapy delivery datatime stamps, the diagnostic diabetes test data time stamps and thevalues corresponding to meals to determine which of the meals therespective diabetes therapy delivery events are most closely related intime, and to determine whether at least one of the diagnostic diabetestests is a pre-meal event or a post-meal event based on the time stampof the diagnostic diabetes test relative to the diabetes therapydelivery data time stamps and their corresponding related meals, and thecomputer generating an output indicative of the determined one of apre-meal event or a post-meal event.
 2. The method as claimed in claim1, wherein analyzing comprises allocating the time stamps correspondingto a diabetes therapy delivery event comprising associating the diabetestherapy delivery event with a first meal of the day if its time stamp isbefore the first meal of the day, associating the diabetes therapydelivery event with a second meal of the day if its time stamp is afterthe first meal of the day and before the second meal, associating thediabetes therapy delivery event with a third meal of the day if its timestamp is after the second meal of the day and before the third meal, andassociating the diabetes therapy delivery event with bedtime if its timestamp is after the third meal of the day and before bedtime.
 3. Acomputer-implemented method of processing diagnostic data comprising:receiving diabetes therapy delivery data and corresponding time stampsfor when different diabetes therapy delivery events were administered toa patient; receiving diagnostic diabetes test data and correspondingtime stamps for when diagnostic diabetes tests were administered to thepatient; receiving a value corresponding to a typical number of mealseaten per day; and analyzing by performing cluster analysis, using thecomputer, of the diabetes therapy delivery data time stamps, thediagnostic diabetes test data time stamps and the number of meals eatenper day to determine how the therapy data time stamps and the diagnostictest data time stamps cluster relative to the number of meals eaten perday for segmenting a day into mealtimes and to determine whether atleast one of the diagnostic diabetes tests is a pre-meal event or apost-meal event based on the time stamp of the diagnostic diabetes testrelative to the diabetes therapy delivery data time stamps and theircorresponding mealtimes indicated via the cluster analysis, and thecomputer generating an output indicative of the determined one of apre-meal event or a post-meal event.
 4. The method as claimed in claim3, wherein the cluster analysis employs determining average times of atleast one of the diabetes therapy delivery data time stamps and thediagnostic diabetes test data time stamps and a selected measure of atleast one of confidence interval and variation around the average timesto determine how the diabetes therapy delivery data time stamps and thediagnostic diabetes test data time stamps cluster relative to the numberof meals eaten per day for segmenting a day into mealtimes.
 5. Themethod as claimed in claim 1 or 3, wherein analyzing comprises applyinga set of timing thresholds comprising categorizing the time stampscorresponding to the diagnostic diabetes tests that are less than orequal to a selected number A of minutes before a diabetes therapydelivery event as “pre-meal,” categorizing the time stamps correspondingto the diagnostic diabetes tests that are greater than or equal to aselected number B of minutes AND less than or equal to a selected numberof C minutes after the diabetes therapy delivery event as “post-meal,”and categorizing the time stamps corresponding to the diagnosticdiabetes tests that are less than or equal to a selected number D ofminutes before the diabetes therapy delivery event AND are greater thanor equal to C minutes after the previous diabetes therapy delivery eventas “pre-meal,” wherein A, B, C and D are time values and A<B<C andA<D<B.
 6. The method as claimed in claim 1 or 3, wherein the time stampsalso comprise dates and further comprising: receiving feedback data froma patient regarding accuracy of the categorizing of the diagnosticdiabetes tests as pre-meal or post-meal; employing an iterative learningalgorithm that analyzes the dates and time stamps corresponding to thediabetes therapy delivery data and the diagnostic diabetes test data anduses the feedback on successive analyses to improve the categorizing ofthe diagnostic diabetes test as pre-meal or post-meal over time.
 7. Themethod as claimed in claim 1 or 3, wherein the diabetes therapy deliveryevent is an insulin injection and the diagnostic diabetes test is ablood glucose test.
 8. The method as claimed in claim 1 or 3, whereinthe analyzing is performed via the computer in one of a blood glucosemeter and a repository in two-way communication with a blood glucosemeter.
 9. The method as claimed in claim 1 or 3, further comprisingreceiving exercise data relating to exercise activity of the patient,further comprising processing the exercise data and at least one of thediabetes therapy delivery data, the diagnostic diabetes test data, anddata relating to meals eaten by the patient to determine when a changein at least one of diabetes therapy delivery to the patient andfrequency of diagnostic diabetes tests are needed to regulate diagnosticdiabetes test levels of the patient, the processing being performed viathe computer in one of a blood glucose meter, a repository in two-waycommunication with a blood glucose meter, a personal computer, a cellphone, and a portable processing device.
 10. The method as claimed inclaim 5, wherein A corresponds to substantially 30 minutes, Bcorresponds to substantially 90 minutes, C corresponds to substantially180 minutes, and D corresponds to substantially 45 minutes.
 11. Anon-transitory computer-readable medium storing a program for processingdiagnostic data comprising diabetes therapy delivery data andcorresponding time stamps for when different diabetes therapy deliveryevents were administered to a patient, and diagnostic diabetes test dataand corresponding time stamps for when diagnostic diabetes tests wereadministered to the patient, the program comprising: a first set ofinstructions for analyzing the diabetes therapy delivery data timestamps, the blood glucose test data time stamps and a valuecorresponding to a typical number of meals eaten by the patient in a dayto determine which of the meals the respective diabetes therapy deliveryevents are most closely related in time, and to determine whether atleast one of the diagnostic diabetes tests is a pre-meal event or apost-meal event based on the time stamp of the diagnostic diabetes testrelative to the diabetes therapy delivery data time stamps and theircorresponding related meals, and generating an output indicative of thedetermined one of a pre-meal event or a post-meal event.